This session will show how we implemented a solution to support high-frequency data ingestion from smart meters. We implemented a robust API endpoint that interfaces directly with IoT devices. This API processes messages in real time from millions of distributed IoT devices and meters across the network. The architecture leverages cloud storage as a landing zone for the raw data, followed by a streaming pipeline built on Lakeflow Declarative Pipelines. This pipeline implements a multi-layer medallion architecture to progressively clean, transform and enrich the data. The pipeline operates continuously to maintain near real-time data freshness in our gold layer tables. These datasets connect directly to Databricks Dashboards, providing stakeholders with immediate insights into their operational metrics. This solution demonstrates how modern data architecture can handle high-volume IoT data streams while maintaining data quality and providing accessible real-time analytics for business users.

In today’s logistics landscape, operational continuity depends on real time awareness and proactive decision making. This session presents an AI agent driven solution built on Databricks that transforms real time fleet IoT data into autonomous workflows. Streaming telemetry such as bearing vibration data is ingested and analyzed using FFT to detect anomalies. When a critical pattern is found, an AI agent diagnoses root causes and simulates asset behavior as a digital twin, factoring in geolocation, routing, and context. The agent then generates a corrective strategy by identifying service sites, skilled personnel, and parts, estimating repair time, and orchestrating reroutes. It evaluates alternate delivery vehicles and creates transfer plans for critical shipments. The system features human AI collaboration, enabling teams to review and execute plans. Learn how this architecture reduces downtime and drives resilient, adaptive fleet management.

The book explores the fundamental principles and transformative advancements in cutting-edge algorithmic technologies, detailing their application and impact on revolutionizing healthcare. This book provides an in-depth account of how technologies such as artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) are reshaping healthcare, transitioning from traditional diagnostic and treatment approaches to data-driven solutions that improve predictive accuracy and patient outcomes. The text also addresses the challenges and considerations associated with adopting these technologies, including ethical implications, data security concerns, and the need for human-centered approaches in algorithmic medicine. After introducing digital twin technology and its potential to enhance healthcare delivery, the book examines the broader effects of digital technology on the healthcare system. Subsequent chapters explore topics such as innovations in medical imaging, predictive analytics for improved patient outcomes, and deep learning algorithms for brain tumor detection. Other topics include generative adversarial networks (GANs), convolutional neural networks (CNNs), smart wearables for remote patient monitoring, effective IoT solutions, telemedicine advancements, and blockchain security for healthcare systems. The integration of biometric systems driven by AI, securing cyber-physical systems in healthcare, and digitizing wellness through electronic health records (EHRs) and electronic medical records (EMRs) are also discussed. The book concludes with an extensive case study comparing the impacts of various healthcare applications, offering insights and encouraging further research and innovation in this dynamic field. Audience This book is suitable for academicians and professionals in health informatics, bioinformatics, biomedical science and engineering, artificial intelligence, as well as clinicians, IT specialists, and policymakers in healthcare.

In Anbetracht von Milliarden vernetzter IoT-Geräte, die riesige Datenmengen erzeugen, stehen Entwickler vor der enormen Herausforderung, die Informationen in Erkenntnisse umzuwandeln. Datenvisualisierung kann dieser Komplexität einen Sinn geben, indem sie uns hilft, Datenmuster und -beziehungen auf intuitive Weise zu verstehen. In diesem Vortrag wird die 3D-Visualisierung als ein besonders nützliches Werkzeug für die Schaffung immersiver, interaktiver Erlebnisse vorgestellt. Zu den besprochenen Schlüsselkonzepten gehören die Datenmodellierung, die Auswahl der richtigen Visualisierungstechniken, die Erstellung von 3D-Umgebungen, die Implementierung dynamischer Aktualisierungen und die Optimierung.

Die Anwendung von KI-Modellen wird zunehmend benutzerfreundlicher und für jedermann zugänglich. Dies erweist sich insbesondere in der aufstrebenden Welt des Internet of Things (IoT) als äußerst bedeutsam. Die Verschmelzung dieser beiden Technologien eröffnet faszinierende, neue Möglichkeiten, um bedeutende Erkenntnisse aus den eigenen Daten zu gewinnen. Doch wie es oft der Fall ist, gestaltet sich der Einstieg nicht immer ganz leicht. Aus diesem Grund erklären wir euch in diesem Talk nicht nur die notwendigen Fachbegriffe, sondern erarbeiten die praktisch relevanten Schlüsselkonzepte im Code - ganz ohne höhere Mathematik und geben euch so einen AI-Kickstart mit Python und C#. Also ran an die Jupyter Notebooks und starte mit uns eine Reise in die wundervolle Welt der künstlichen Intelligenz und finde heraus welche Actions und Insights in deinen Sensordaten schlummern!

A conversation with millions of researched Cyber-Physical Systems… With billions of IoT and OT devices powering manufacturing and industrial operations today, the xTended Internet of Things (xIoT) now surpasses traditional endpoints by an order of magnitude. Despite their critical roles, many of these IoT and OT Cyber-Physical Systems (CPS) remain overlooked and unsecured—operating with default or weak credentials, outdated firmware, insecure configurations, and an end-of-life state. This creates a vast and vulnerable attack surface that threat actors increasingly target to disrupt operations, exfiltrate data, or stage sophisticated ransomware attacks. Attendees will leave with a deeper understanding of the scope and state of this attack surface, the critical role IoT and OT security plays in protecting the modern industrial landscape, and actionable steps that can be taken to strengthen their xIoT security posture.

With billions of IoT and OT devices powering manufacturing and industrial operations today, the xTended Internet of Things (xIoT) now surpasses traditional endpoints by an order of magnitude. Despite their critical roles, many of these IoT and OT Cyber-Physical Systems (CPS) remain overlooked and unsecured—operating with default or weak credentials, outdated firmware, insecure configurations, and an end-of-life state. This creates a vast and vulnerable attack surface that threat actors increasingly target to disrupt operations, exfiltrate data, or stage sophisticated ransomware attacks. The session will also delve into the anatomy of OT and OT-adjacent IoT cyberattacks, detailing how attackers exploit these devices to achieve malicious goals. A live hacking demonstration will showcase the methods used to compromise common, yet mission-critical, devices — emphasizing the importance of proactive security measures to disappoint bad actors. Attendees will leave with a deeper understanding of the scope and state of this attack surface, the critical role IoT and OT security plays in protecting the modern industrial landscape, and actionable steps that can be taken to strengthen their xIoT security posture.

Exploration of xIoT/OT devices, security vulnerabilities, and a live hacking demonstration with actionable security steps.

With billions of IoT and OT devices powering manufacturing and industrial operations today, the xTended Internet of Things (xIoT) now surpasses traditional endpoints by an order of magnitude. Despite their critical roles, many of these IoT and OT Cyber-Physical Systems (CPS) remain overlooked and unsecured—operating with default or weak credentials, outdated firmware, insecure configurations, and an end-of-life state. This creates a vast and vulnerable attack surface that threat actors increasingly target to disrupt operations, exfiltrate data, or stage sophisticated ransomware attacks. The session will also delve into the anatomy of OT and OT-adjacent IoT cyberattacks, detailing how attackers exploit these devices to achieve malicious goals. A live hacking demonstration will showcase the methods used to compromise common, yet mission-critical, devices — emphasizing the importance of proactive security measures to disappoint bad actors. Attendees will leave with a deeper understanding of the scope and state of this attack surface, the critical role IoT and OT security plays in protecting the modern industrial landscape, and actionable steps that can be taken to strengthen their xIoT security posture.

We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here. Edge computing is poised to transform industries by bringing computation and data storage closer to the source of data generation. This shift unlocks new types of value creation with data & AI and allows for a privacy-first and deeply personalized use of AI on our devices. What will the edge computing transition look like? How do you ensure applications are edge-ready, and what is the role of AI in the transition?  Derek Collison is the founder and CEO at Synadia. He is an industry veteran, entrepreneur and pioneer in large-scale distributed systems and cloud computing. Derek founded Synadia Communications and Apcera, and has held executive positions at Google, VMware, and TIBCO Software. He is also an active angel investor and a technology futurist around Artificial Intelligence, Machine Learning, IOT and Cloud Computing. Justyna Bak is VP of Marketing at Synadia. Justyna is a versatile executive bridging Marketing, Sales and Product, a spark-plug for innovation at startups and Fortune 100 and a tech expert in Data Analytics and AI, AppDev and Networking. She is an astute influencer, panelist and presenter (Google, HBR) and a respected leader in Silicon Valley and Europe. In the episode, Richie, Derek, and Justyna explore the transition from cloud to edge computing, the benefits of reduced latency, real-time decision-making in industries like manufacturing and retail, the role of AI at the edge, and the future of edge-native applications, and much more. Links Mentioned in the Show: SynadiaConnect with Derek and JustynaCourse: Understanding Cloud ComputingRelated Episode: The Database is the Operating System with Mike Stonebraker, CTO & Co-Founder At DBOSRewatch sessions from RADAR: Forward Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The world of SAP is undergoing a major transformation, with many customers either planning or actively modernizing their SAP landscapes as part of the S/4HANA digital transformation. Given the extensive SAP transformation efforts adopted by nearly all SAP customers in recent years and the profound impact these digital changes have had on their business models and IT organizations, the authors decided to write this book. As customers embark on their SAP on AWS journey, they face three main challenges: deciding on the overall strategy, selecting the right business use cases and implementing them effectively. This book aims to address these challenges by guiding readers through the process of identifying and executing the appropriate use cases. It will highlight how customers can harness AWS services beyond merely hosting their SAP systems on AWS, demonstrating the potential of these services to drive innovation. This book covers the entire journey, from defining strategy and identifying business use cases to their implementation, providing practical tips, strategies, and insights. It serves as an essential guide for customers planning to migrate or those who have already migrated their SAP workloads to AWS, helping them explore beyond just the infrastructure aspects of their journey. You Will : Discover how to go beyond just hosting SAP systems on AWS, using the full range of AWS services to innovate and extend your SAP applications. Learn how to identify the right business use cases and implement them effectively, with practical examples and real-world scenarios. Develop the mindset and skills needed to architect modern, cloud-native, event-driven architectures, balancing trade-offs between simplicity, efficiency, and cost. This book is for: Business leaders, IT professionals, and SAP specialists who are looking to modernize their SAP landscapes by leveraging AWS services

Von Predictive Maintenance bis zum selbstoptimierenden Produktionsprozess - die Verknüpfung von Software und physischen Geräten mittels IoT bietet uns enorme Innovationspotenziale. Digitale Zwillinge sind dabei ein Grundbaustein jeder effizienten Bestrebung, diese Potenziale auszuschöpfen. Ohne den Einsatz digitaler Zwillinge führen IoT-Entwicklungen leider sehr schnell zu einer komplexen und unübersichtlichen Systemlandschaft, welche die Realisierung von Innovationen nur mit sehr hohem Investment ermöglicht – ein Widerspruch zur schnelllebigen Welt, in der sich moderne Unternehmen heutzutage befinden. Die große Herausforderung besteht dabei im enormen Programmieraufwand, der nötig ist, um verschiedene Software-Komponenten mit den unterschiedlichen Kommunikationsprotokollen und Austauschformaten von Geräten und deren Simulationen zu integrieren. Fehlende Wiederverwendbarkeit im IoT führt außerdem oft dazu, dass dieser Aufwand mit der Größe eines Systems enorm ansteigt. In meinem Vortrag zeige ich, wie uns der Einsatz digitaler Zwillinge schon heute ermöglicht, den Entwicklungs- und Wartungsaufwand von IoT-Anwendungen gering zu halten. Ich veranschauliche dabei den Einsatz digitaler Zwillinge und deren Vorteile anhand von öffentlich zugänglichen Beispielen aus dem Bereich Smart Home. Außerdem gehe ich darauf ein, welche Hindernisse die Etablierung digitaler Zwillinge in der Praxis aktuell noch schwer machen, und welche Geschäftsmodelle sich aus diesen Hindernissen ergeben.

We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here. Staying ahead means knowing what’s happening right now—not minutes or hours later. Real-time analytics promises to help teams react faster, make informed choices, and even predict issues before they arise. But implementing these systems is no small feat, and it requires careful alignment between technical capabilities and business needs. How do you ensure that real-time data actually drives impact? And what should organizations consider to make sure their real-time analytics investments lead to tangible benefits? Zuzanna Stamirowska is the CEO of Pathway.com - the fastest data processing engine on the market which makes real-time intelligence possible. Zuzanna is also the author of the state-of-the-art forecasting model for maritime trade published by the National Academy of Sciences of the USA. While working on this project she saw that the digitization of traditional industries was slowed down by the lack of a software infrastructure capable of doing automated reasoning on top of data streams, in real time. This was the spark to launch Pathway. She holds a Master’s degree in Economics and Public Policy from Sciences Po, Ecole Polytechnique, and ENSAE, as well as a PhD in Complexity Science.. Hélène Stanway is Independent Advisor & Consultant at HMLS Consulting Ltd. Hélène is an award-winning and highly effective insurance leader with a proven track record in emerging technologies, innovation, operations, data, change, and digital transformation. Her passion for actively combining the human element, design, and innovation alongside technology has enabled companies in the global insurance market to embrace change by achieving their desired strategic goals, improving processes, increasing efficiency, and deploying relevant tools. With a special passion for IoT and Sensor Technology, Hélène is a perpetual learner, driven to help delegates succeed.  In the episode, Richie, Zuzanna and Hélène explore real-time analytics, their operational impact, use-cases of real-time analytics across industries, the benefits of adopting real-time analytics, the key roles and stakeholders you need to make that happen, operational challenges, strategies for effective adoption, the real-time of the future, common pitfalls, and much more.  Links Mentioned in the Show:

Pathway

Connect with Zuzanna and HélèneLiArticle: What are digital twins and why do we need them?Course: Time Series Analysis in Power BIRelated Episode: How Real Time Data Accelerates Business Outcomes with George TrujilloSign up to RADAR: Forward Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data

Discussion en fireside chat sur la création d'émotions dans le développement de produits physiques, avec Pierre Garner, Grégoire Markarian et Clémence Gueidan. Comment le design peut susciter des émotions et enrichir l'expérience utilisateur, comment concilier l'héritage d'un design iconique avec la nécessité d'innover, et les défis spécifiques à la création de produits physiques par rapport au numérique.

Computational Intelligence in Sustainable Computing and Optimization: Trends and Applications focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in applications, such as agriculture, biomedical systems, bioinformatics, business intelligence, economics, disaster management, e-learning, education management, financial management, and environmental policies. The book presents research in sustainable computing and optimization, combining methods from engineering, mathematics, artificial intelligence, and computer science to optimize environmental resources Computational intelligence in the field of sustainable computing combines computer science and engineering in applications ranging from Internet of Things (IoT), information security systems, smart storage, cloud computing, intelligent transport management, cognitive and bio-inspired computing, and management science. In addition, data intelligence techniques play a critical role in sustainable computing. Recent advances in data management, data modeling, data analysis, and artificial intelligence are finding applications in energy networks and thus making our environment more sustainable. Presents computational, intelligence–based data analysis for sustainable computing applications such as pattern recognition, biomedical imaging, sustainable cities, sustainable transport, sustainable agriculture, and sustainable financial management Develops research in sustainable computing and optimization, combining methods from engineering, mathematics, and computer science to optimize environmental resources Includes three foundational chapters dedicated to providing an overview of computational intelligence and optimization techniques and their applications for sustainable computing

The convergence of Artif icial Intelligence (AI) and Internet of Things (IoT) is reshaping the way industries, businesses, and economies function; the 34 chapters in this collection show how the full potential of these technologies is being enabled to create intelligent machines that simulate smart behavior and support decision-making with little or no human interference, thereby providing startling organizational efficiencies. Readers will discover that in Reshaping Intelligent Business and Industry: The book unpacks the two superpowers of innovation, AI and IoT, and explains how they connect to better communicate and exchange information about online activities; How the center and the network's edge generate predictive analytics or anomaly alerts; The meaning of AI at the edge and IoT networks. How bandwidth is reduced and privacy and security are enhanced; How AI applications increase operating efficiency, spawn new products and services, and enhance risk management; How AI and IoT create 'intelligent' devices and how new AI technology enables IoT to reach its full potential; Analyzes AIOT platforms and the handling of personal information for shared frameworks that remain sensitive to customers’ privacy while effectively utilizing data. Audience This book will appeal to all business and organization leaders, entrepreneurs, policymakers, and economists, as well as scientists, engineers, and students working in artificial intelligence, software engineering, and information technology.

Show Notes  The Data Product Management In Action podcast, brought to you by Soda and executive producer Scott Hirleman, is a platform for data product management practitioners to share insights and experiences.  In Season 01, Episode 18, our host Frannie Helforoush is back again interviewing Katy Pusch about her extensive experience in data product management, particularly with decision-support data products. Katy shares her insights on incorporating machine learning and analytics to empower stakeholders in making informed decisions. They both explore team structure, the challenges encountered in product development, and the critical importance of validating products with users to ensure their effectiveness. About our host Frannie Helforoush: Frannie's journey began as a software engineer and evolved into a strategic product manager. Now, as a data product manager, she leverages her expertise in both fields to create impactful solutions. Frannie thrives on making data accessible and actionable, driving product innovation, and ensuring product thinking is integral to data management. Connect with Frannie on LinkedIn. About our guest Katy Pusch: Katy brings more than a decade of experience in product management and market strategy, driving market change and adoption of innovative technology solutions. She has successfully built and launched data products, IoT solutions, and SaaS platforms in multiple industries such as healthcare, education, and real estate. She is currently serving as a Sr.Product Line Director at Trintech. With a background in research, she brings data science and market intelligence to every aspect of her work. Katy is passionate about data privacy and tech-ethics, and is pursuing an MS in History and Sociology of Technology and Science at GeorgiaTech. When she’s not working with her team to deliver top solutions, Katy enjoys spending time with her husband, building Lego models, and pursuing a private pilot license. Connect with Katy on LinkedIn. All views and opinions expressed are those of the individuals and do not necessarily reflect their employers or anyone else.  Join the conversation on LinkedIn.  Apply to be a guest or nominate someone that you know.  Do you love what you're listening to? Please rate and review the podcast, and share it with fellow practitioners you know. Your support helps us reach more listeners and continue providing valuable insights!              

One of the most annoying conversations about data that happens far too often is: “Can you do an analysis and answer this business problem for me?” “Sure, where’s the data?” “I don’t know. Probably in one of our databases.” At this point more time is spent hunting for data than actually analyzing it. Rather than grumbling about it, it would obviously be more productive to learn how to solve data discoverability issues. What’s the best way to properly document data sets? How can you avoid spending all your time maintaining dashboards that no one actually uses?  Shinji Kim is the Founder & CEO of Select Star, an automated data discovery platform that helps you understand your data. Previously, she was the CEO of Concord Systems (concord.io), a NYC-based data infrastructure startup acquired by Akamai Technologies in 2016. She led building Akamai’s new IoT data platform for real-time messaging, log processing, and edge computing. Prior to Concord, Shinji was the first Product Manager hired at Yieldmo, where she led the Ad Format Lab, A/B testing, and yield optimization. Before Yieldmo, she was analyzing data and building enterprise applications at Deloitte Consulting, Facebook, Sun Microsystems, and Barclays Capital. Shinji studied Software Engineering at University of Waterloo and General Management at Stanford GSB. She advises early stage startups on product strategy, customer development, and company building. In the episode, Richie and Shinji explore the importance of data governance, the utilization of data, data quality, challenges in data usage, why documentation matters, metadata and data lineage, improving collaboration between data and business teams, data governance trends to look forward to, and much more.  Links Mentioned in the Show: Select StarConnect with Shinji[Course] Data Governance ConceptsRelated Episode: Making Data Governance Fun with Tiankai Feng, Data Strategy & Data Governance Lead at ThoughtWorksRewatch sessions from RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile app Empower your business with world-class data and AI skills with DataCamp for business

The surging predictive analytics market is expected to grow from $10.5 billion today to $28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward-thinking companies. If you're a data professional, you need to be aligned with your company's business activities more than ever before. This practical book provides the background, tools, and best practices necessary to help you design, implement, and operationalize predictive analytics on-premises or in the cloud. Explore ways that predictive analytics can provide direct input back to your business Understand mathematical tools commonly used in predictive analytics Learn the development frameworks used in predictive analytics applications Appreciate the role of predictive analytics in the machine learning process Examine industry implementations of predictive analytics Build, train, and retrain predictive models using Python and TensorFlow

X509 certificates and Google Cloud Certificate Authority Service offer powerful authentication solutions for workloads, micro-services, and smart devices. This session will guide you through the latest innovations in certificate provisioning and management for VMs, Kubernetes, and Load Balancers. We'll delve into SPIFFE, mTLS, and service-to-service authentication techniques. Gain real-world insights from Signify (formerly Philips Lighting) and see how they've implemented Google Cloud Certificate Authority Service and the Matter standard within their IoT ecosystem.

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